ACM Transactions on Interactive Intelligent Systems

Papers
(The H4-Index of ACM Transactions on Interactive Intelligent Systems is 16. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2021-05-01 to 2025-05-01.)
ArticleCitations
Learning GUI Completions with User-defined Constraints309
Adaptive Cognitive Training with Reinforcement Learning61
Tribe or Not? Critical Inspection of Group Differences Using TribalGram49
The Author’s Journey—Understanding and Improving the Authoring Process of Theory-Driven Socially Intelligent Agents48
How Should an AI Trust its Human Teammates? Exploring Possible Cues of Artificial Trust41
Effects of Explanations in AI-Assisted Decision Making: Principles and Comparisons40
How Do Users Experience Traceability of AI Systems? Examining Subjective Information Processing Awareness in Automated Insulin Delivery (AID) Systems40
Predicting Group Choices from Group Profiles30
Unpacking Human-AI interactions: From Interaction Primitives to a Design Space28
ClioQuery : Interactive Query-oriented Text Analytics for Comprehensive Investigation of Historical News Archives27
-generAItor: Tree-in-the-loop Text Generation for Language Model Explainability and Adaptation25
EDAssistant: Supporting Exploratory Data Analysis in Computational Notebooks with In Situ Code Search and Recommendation23
Reassuring, Misleading, Debunking: Comparing Effects of XAI Methods on Human Decisions21
Comparative Analysis of Personality Recognition in Response to Virtual Reality and Two-Dimensional Emotional Stimulus Using ECG Signals19
An Empirical Study of Older Adult’s Voice Assistant Use for Health Information Seeking18
HAIFAI: H uman- AI Interaction for Mental F ace Reconstruct i on16
AOI-shapes: An Efficient Footprint Algorithm to Support Visualization of User-defined Urban Areas of Interest16
Crowdsourcing Thumbnail Captions: Data Collection and Validation16
Towards Understanding AI Delegation: The Role of Self-Efficacy and Visual Processing Ability16
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